Computer Science 163/265, Spring 2016:
General Course Information
The course meets Monday, Wednesday, and Fridays, 2:00 - 2:50
in Bren Hall, room 1100. Prof. Eppstein's office hours are Mondays and Wednesdays from 4:00 - 5:00 (or by
appointment) in Bren 4082. The teaching assistant is Nitin Agarwal,
office hours Tuesdays 3:00 - 4:00 in DBH 3013 and Wednesdays 5:00 - 6:00
in DBH 4011. We also have two readers, Shu Kong and Jia Chen.
Coursework will consist of weekly homeworks, a midterm, and a
comprehensive final exam. Group work on homeworks is permitted;
each student should turn in his or her own copy of the homeworks. The
undergraduate (163) and graduate (265) courses will share lectures, and
some homework problems; however, the graduate course will have
additional homework problems and different exams. Homeworks will typically be assigned on Fridays and due on the following Friday,
electronically in PDF format via the eee web site.
The text we will be using is Graph
Algorithms, a collection of readings compiled from
Wikipedia. Lecture materials will not be distributed to the class; instead, you are encouraged to attend the lecture yourself and take your own notes. Recording the lectures for your own personal use is allowed, but other uses of recorded lectures (including making them available online) is forbidden.
The final grade will be formed by combining the numerical scores from
the homeworks (20%), midterm (35%), and final (45%).
For the UCI honesty policy, please see honesty.uci.edu. Students who are caught cheating in this class (for instance by copying exam solutions or allowing other students to copy from them) risk getting an F in the class or other disciplinary action as allowed by this policy.
Tentative Schedule of Topics
- Week 1.
- Web crawler case study. PageRank
algorithm. DFS, BFS, Tarjan's
algorithm for strongly connected
components. Representation of graphs.
- Homework 1, Due Friday, April 8.
- Week 2.
and river network simulation via invasion percolation case
spanning trees, Prim-Dijkstra-Jarnik
voting case study and
- Homework 2, Due Friday, April 15.
- Week 3.
- No class Monday, April 11, or Wednesday, April 13.
- DAGs and
- Homework 3, Due Friday, April 22.
- Week 4.
- Road map path planning case study.
distance based distance estimation,
landmark-based distance estimation.
- Homework 4, Due Friday, April 29.
- Week 5.
- Transportation scheduling case study.
Travelling salesman problem.
- Exponential-time dynamic programming for the TSP,
approximation algorithms and the approximation ratio,
- Week 6.
- Midterm, Monday, May 2.
elimination case study. Maximum flow
problem, minimum cut
min-cut theorem, augmenting
path (Ford-Fulkerson) algorithm.
- Week 7.
school residency assignment case study. Matchings, stable
algorithm for stable marriage.
graphs, formulating bipartite maximum matching as a flow problem,
using matchings to find vertex covers,
partition into a minimum number
- Week 8.
- Register allocation case study.
and perfect graphs.
breadth-first search to find an elimination ordering.
- Guest lecture Friday, May 20
- Week 9.
- Social network analysis case study.
properties: sparsity, small
laws. Barabási-Albert model.
and k-cores, h-index
based dynamic triangle counting algorithm.
bound on maximal cliques, Bron-Kerbosch
- Week 10.
- Memorial day holiday, Monday, May 30.
graphs; review of planarity-related topics from earlier weeks (graph
drawing, road maps, invasion percolation via minimum spanning trees of
grid graphs, graph coloring and the four-color theorem).
duality of Euler
tours and bipartiteness,
greedy 6-coloring, Boruvka in linear time.
Planarity testing, Fáry's theorem and
straight-line embedding algorithm.
- Finals week
- Final examination (cumulative), Wednesday, Jun 8, 10:30-12:30.
Material from Previous Course Offerings
The syllabus from Spring 2015 has more links, to syllabi and exams from earlier quarters.